Energy Conservation for Datacenters in Cloud Computing using Genetic Algorithms

In recent developments most of the organizations are focused on reduce the investment to the work environment and important concern, how to design the infrastructure and how to utilize maximum resources. The optimization of energy consumption is important concern for design of day to day life and future computing and distinguish techniques to improve performance of workload demand in the dynamic environment such grids, clusters and clouds. This paper proposes an improved genetic algorithm based on time cost and energy consumption models and we use the Dynamic Voltage scaling (DVS) and Dynamic voltage frequency scaling (DVFS) methodologies for reduce energy consumption and determine the optimal placement of virtual machines in order to maximize the overall renewable energy usage and minimize the energy consumption.